Hair styles system for rendering hair strands based on hair spline data

ABSTRACT

Systems and methods are provided for rendering hair. The systems and methods include receiving hair spline data comprising coordinates of a plurality of hair strands; selecting a first hair strand of the plurality of hair strands; retrieving coordinates of the first hair strand; identifying based on the respective coordinates of the plurality of hair strands a second hair strand that is adjacent to the first hair strand; storing a reference to the second hair strand in association with the coordinates of the first hair strand; and generating one or more additional hair strands between the first hair strand and the second hair strand based on the coordinates of the first hair strand and the reference to the second hair strand.

CLAIM OF PRIORITY

This application is a continuation of U.S. patent application Ser. No.17/313,388, filed on May 6, 2021, which is a continuation of U.S. patentapplication Ser. No. 16/532,221, filed on Aug. 5, 2019, each of which isincorporated herein by reference in its entirety.

TECHNICAL FIELD

The present disclosure relates generally to hair simulation andrendering.

BACKGROUND

Modern day user devices enable users to graphically enhance and modifyimages of objects depicted in a video stream or images. For example,users can add makeup and change various attributes of a face depicted inan image or video. After making the enhancements or modifications, themodified video stream or images can be shared with other users over asocial network.

BRIEF DESCRIPTION OF THE DRAWINGS

The patent or application file contains at least one drawing executed incolor. Copies of this patent or patent application publication withcolor drawing(s) will be provided by the Office upon request and paymentof the necessary fee.

In the drawings, which are not necessarily drawn to scale, like numeralsmay describe similar components in different views. To easily identifythe discussion of any particular element or act, the most significantdigit or digits in a reference number refer to the figure number inwhich that element is first introduced. Some embodiments are illustratedby way of example, and not limitation, in the figures of theaccompanying drawings in which.

FIG. 1 is a block diagram showing an example messaging system forexchanging data (e.g., messages and associated content) over a network,according to example embodiments.

FIG. 2 is a schematic diagram illustrating data which may be stored inthe database of a messaging server system, according to exampleembodiments.

FIG. 3 is a schematic diagram illustrating a structure of a messagegenerated by a messaging client application for communication, accordingto example embodiments.

FIG. 4 is a block diagram showing an example hair rendering system,according to example embodiments.

FIGS. 5 and 6 are flowcharts illustrating example operations of the hairrendering system, according to example embodiments.

FIGS. 7A, 7B, 8A and 8B are illustrative inputs and outputs of the hairrendering system, according to example embodiments.

FIG. 9 is a block diagram illustrating a representative softwarearchitecture, which may be used in conjunction with various hardwarearchitectures herein described, according to example embodiments.

FIG. 10 is a block diagram illustrating components of a machine able toread instructions from a machine-readable medium (e.g., amachine-readable storage medium) and perform any one or more of themethodologies discussed herein, according to example embodiments.

DETAILED DESCRIPTION

The description that follows includes systems, methods, techniques,instruction sequences, and computing machine program products thatembody illustrative embodiments of the disclosure. In the followingdescription, for the purposes of explanation, numerous specific detailsare set forth in order to provide an understanding of variousembodiments. It will be evident, however, to those skilled in the art,that embodiments may be practiced without these specific details. Ingeneral, well-known instruction instances, protocols, structures, andtechniques are not necessarily shown in detail.

Typical systems allow users to enhance and modify objects, such asfaces, depicted in images. The number and types of modifications madeavailable to users continue to grow in complexity. More complexmodifications place heavier burdens on the underlying resources, whichtake away processing power from other applications that run on thedevices and drain power resources at a rapid pace. This is especially aconcern when such complex image modification techniques are implementedand used on mobile devices where power and processing resources arelimited. In such cases, users try to avoid degrading performance ofapplications running on their devices and draining the power resources,such as batteries. As a result, complex image modification features mayend up not being used and waste resources.

The disclosed embodiments improve the efficiency of using the electronicdevice by providing a hair rendering system that provides a user withthe option of enhancing and modifying hair of an object, such as hair ona user's head depicted in an image or video frames. The disclosedembodiments enable the user to enhance and modify hair of the object onmobile devices in real-time in an efficient manner that does not degradeprocessing or battery resources of the mobile device. To do so, thedisclosed embodiments process received hair spline data to generate andsimulate additional hair strands between two or more neighboring hairstrands. To reduce the storage and processing requirements, according tosome embodiments, positions of the neighboring hair strands are storedas indices in association with a given hair strand. For example, a floattexture file that includes red, green, blue, and alpha channels for eachhair strand is generated, where the red, green and blue channels storecoordinates of a given hair strand and the alpha channel stores one ormore indices of (or one or more references to) one or more neighboringhair strands. Specifically, the float texture file may include aplurality of sections that include red, green, blue and alpha channels,each section being associated with a difference hair strand. Eachsection of the plurality of sections includes coordinates of the givenhair strand stored in the red, green and blue channels and optionallyone or more references to one or more other sections that storecoordinates of other hair strands. The float texture file is thenprocessed to generate and simulate additional hair strands to enhancethe realistic effect of a hair model.

Specifically, according to the disclosed embodiments, hair spline datais received that includes coordinates of a plurality of hair strands.The disclosed techniques automatically generate additional hair strandsin an efficient manner by selecting a first hair strand of the pluralityof hair strands; retrieving coordinates of the first hair strand;searching coordinates of the plurality of hair strands, based on thecoordinates of the first hair strand, to identify a second hair strandof the plurality of hair strands that is adjacent to the first hairstrand; and storing an index of or reference to the second hair strandin association the coordinates of the first hair strand. After theadditional hair strands are generated, a hair model is rendered inmultiple phases with a realistic effect.

FIG. 1 is a block diagram showing an example messaging system 100 forexchanging data (e.g., messages and associated content) over a network106. The messaging system 100 includes multiple client devices 102, eachof which hosts a number of applications, including a messaging clientapplication 104 and a third-party application 105. Each messaging clientapplication 104 is communicatively coupled to other instances of themessaging client application 104, the third-party application 105, and amessaging server system 108 via a network 106 (e.g., the Internet).

Accordingly, each messaging client application 104 and third-partyapplication 105 is able to communicate and exchange data with anothermessaging client application 104 and third-party application(s) 105 andwith the messaging server system 108 via the network 106. The dataexchanged between messaging client applications 104, third-partyapplications 105, and the messaging server system 108 includes functions(e.g., commands to invoke functions) and payload data (e.g., text,audio, video, or other multimedia data). Any disclosed communicationsbetween the messaging client application 104 and the third-partyapplication(s) 105 can be transmitted directly from the messaging clientapplication 104 to the third-party application(s) 105 and/or indirectly(e.g., via one or more servers) from the messaging client application104 to the third-party application(s) 105.

The third-party application(s) 105 and the messaging client application104 are applications that include a set of functions that allow theclient device 102 to access a hair rendering system 124. The third-partyapplication 105 is an application that is separate and distinct from themessaging client application 104. The third-party application(s) 105 aredownloaded and installed by the client device 102 separately from themessaging client application 104. In some implementations, thethird-party application(s) 105 are downloaded and installed by theclient device 102 before or after the messaging client application 104is downloaded and installed. The third-party application 105 is anapplication that is provided by an entity or organization that isdifferent from the entity or organization that provides the messagingclient application 104. The third-party application 105 is anapplication that can be accessed by a client device 102 using separatelogin credentials than the messaging client application 104. Namely, thethird-party application 105 can maintain a first user account and themessaging client application 104 can maintain a second user account. Forexample, the third-party application 105 can be a social networkingapplication, a dating application, a ride or car sharing application, ashopping application, a trading application, a gaming application, or animaging application.

In some embodiments, the messaging client application 104 presents agraphical user interface to a user that allows the user to manipulate,modify and/or enhance features of an object, such as the user's face,depicted in an image or video stream. As an example, the graphical userinterface may present a video depicting the user's face. The user canselect a hair style from a list of hair styles presented to the user. Inresponse to receiving the user selection of the hair style, the videodepicting the user's face is modified to replace or overlay the hairportion on top of the user's head with the selected hair style. In someimplementations, the hair style is dynamically adapted and modeled bythe hair rendering system 124. As the user moves their head around inthe video in real-time, the hair rendering system 124 updates andsimulates the selected hair style to appear to move in a realisticmanner. Each hair strand in the selected hair style is updated to moveas the user moves their head, and the updated hair style is displayed inthe video stream depicting the user's face.

In an embodiment, the hair rendering system 124 includes functions forsimulating each of the different hair styles under differentenvironmental conditions (e.g., different movements of the user's head,wind strength, smoothness of the hair, etc.). In an embodiment, the usercan input criteria for controlling how different portions of the hairand/or the hair in its entirety is simulated.

In some embodiments, the modeling of the selected hair style in thevideo stream depicting the user's face can be based on resourcecapabilities of the user device on which the messaging clientapplication 104 is running. For example, the hair rendering system 124may determine whether the user device satisfies certain minimumprocessing capabilities (e.g., whether the user device has access to agraphics library with a first set of functions). If the user device doessatisfy the minimum processing capabilities, then the selected hairstyle is modeled in real-time and each hair strand or group of hairstrands is modeled and updated individually to provide a realisticeffect of the hair moving when subjected to movement of the user's heador certain environmental conditions. If the user device does not satisfythe minimum processing capabilities, then the selected hair style ispresented in the video stream depicting the user face in a staticmanner. In such cases, the hair geometry including all of the hairstrands may be modeled in the same way and may appear to have lessrealistic movement when subjected to movement of the user's head orcertain environmental conditions.

Environmental conditions can include any environmental condition that issensed by the user device and/or that is input by the user. For example,the environmental conditions can include any combination of windinfluence on hair, hair collisions as hair moves, stiffness of the hairindicating a level of how hard each strand of hair is to stretch wheresmaller values indicate softer hair, bend factor indicating how hardeach strand is to bend, twist factor indicating how hard each strand isto twist, collapse factor indicating how hard each strand is tocollapse, air friction factor indicating how fast the motion is to decayto zero, where smaller motion causes the hair to settle faster orslower, gravity factor, wind force factor, etc.

The messaging server system 108 provides server-side functionality viathe network 106 to a particular messaging client application 104. Whilecertain functions of the messaging system 100 are described herein asbeing performed by either a messaging client application 104 or by themessaging server system 108, it will be appreciated that the location ofcertain functionality either within the messaging client application 104or the messaging server system 108 is a design choice. For example, itmay be technically preferable to initially deploy certain technology andfunctionality within the messaging server system 108, but to latermigrate this technology and functionality to the messaging clientapplication 104 where a client device 102 has a sufficient processingcapacity.

The messaging server system 108 supports various services and operationsthat are provided to the messaging client application 104. Suchoperations include transmitting data to, receiving data from, andprocessing data generated by the messaging client application 104. Thisdata may include message content, client device information, geolocationinformation, media annotation and overlays, virtual objects, messagecontent persistence conditions, social network information, and liveevent information, as examples. Data exchanges within the messagingsystem 100 are invoked and controlled through functions available viauser interfaces (UIs) of the messaging client application 104.

Turning now specifically to the messaging server system 108, an APIserver 110 is coupled to, and provides a programmatic interface to, anapplication server 112. The application server 112 is communicativelycoupled to a database server 118, which facilitates access to a database120 in which is stored data associated with messages processed by theapplication server 112.

Dealing specifically with the API server 110, this server 110 receivesand transmits message data (e.g., commands and message payloads) betweenthe client device 102 and the application server 112. Specifically, theAPI server 110 provides a set of interfaces (e.g., routines andprotocols) that can be called or queried by the messaging clientapplication 104 and the third-party application 105 in order to invokefunctionality of the application server 112. The API server 110 exposesvarious functions supported by the application server 112, includingaccount registration; login functionality, the sending of messages, viathe application server 112, from a particular messaging clientapplication 104 to another messaging client application 104 orthird-party application 105; the sending of media files (e.g., images orvideo) from a messaging client application 104 to the messaging serverapplication 114, and for possible access by another messaging clientapplication 104 or third-party application 105; the setting of acollection of media data (e.g., story); the retrieval of suchcollections; the retrieval of a list of friends of a user of a clientdevice 102; the retrieval of messages and content; the adding anddeleting of friends to a social graph; the location of friends within asocial graph; access to user conversation data; access to avatarinformation stored on messaging server system 108; and opening anapplication event (e.g., relating to the messaging client application104).

The application server 112 hosts a number of applications andsubsystems, including a messaging server application 114, an imageprocessing system 116, a social network system 122, and the hairrendering system 124. The messaging server application 114 implements anumber of message processing technologies and functions, particularlyrelated to the aggregation and other processing of content (e.g.,textual and multimedia content) included in messages received frommultiple instances of the messaging client application 104. As will bedescribed in further detail, the text and media content from multiplesources may be aggregated into collections of content (e.g., calledstories or galleries). These collections are then made available, by themessaging server application 114, to the messaging client application104. Other processor- and memory-intensive processing of data may alsobe performed server-side by the messaging server application 114, inview of the hardware requirements for such processing.

The application server 112 also includes an image processing system 116that is dedicated to performing various image processing operations,typically with respect to images or video received within the payload ofa message at the messaging server application 114. A portion of theimage processing system 116 may also be implemented by the hairrendering system 124.

The social network system 122 supports various social networkingfunctions and services and makes these functions and services availableto the messaging server application 114. To this end, the social networksystem 122 maintains and accesses an entity graph within the database120. Examples of functions and services supported by the social networksystem 122 include the identification of other users of the messagingsystem 100 with which a particular user has relationships or is“following” and also the identification of other entities and interestsof a particular user. Such other users may be referred to as the user'sfriends. Social network system 122 may access location informationassociated with each of the user's friends to determine where they liveor are currently located geographically. Social network system 122 maymaintain a location profile for each of the user's friends indicatingthe geographical location where the user's friends live.

The hair rendering system 124 generates hair model simulations forvarious hair styles. To do so, the hair rendering system 124 receivesinput of a hair spline data file that includes coordinates of aplurality of hair strands. The hair rendering system 124 processes thehair strands in the hair spline data file to identify neighbor hairstrands for each of the plurality of hair strands. In some cases, thehair rendering system 124 applies a nearest to current neighbor approachto identify neighboring hair strands for each hair strand. In somecases, the hair rendering system 124 applies a nearest to next neighborapproach to identify neighboring hair strands. In either case, a maximumof two neighbor hair strands is identified for each hair strand. Thehair rendering system 124 updates the hair spline data file to input theindices of (or references to) the identified neighbors of each hairstrand. In some embodiments, the hair rendering system 124 continuouslyupdates the hair spline data file for each frame of a video in which thehair style is selected to be used to modify or enhance an objecteddepicted in the video.

In some cases, the hair rendering system 124 also considers whether anangle formed between the two adjacent hair strands (e.g., a given hairstrand and a neighbor hair strand) is less than a threshold. The hairrendering system 124 conditions whether a particular hair strand can beindexed as a neighbor hair strand to a given hair strand based on theangle that is formed between the two adjacent hair strands. For example,the hair rendering system 124 may determine that the given hair strandis closest in distance to a neighbor hair strand. If the angle formedbetween the given hair strand and the neighbor hair strand is less thanthe threshold, the two hair strands can be indexed as or referenced asneighbors. If the angle formed between the given hair strand and theneighbor hair strand exceeds the threshold, then the neighbor hairstrand is prevented from being indexed with the given hair strand.

In some implementations, the hair rendering system 124 generatesadditional hair strands between each hair strand that is in the hairspline data file and the corresponding one or two neighbors. To generatethe additional hair strands, the hair rendering system 124 appliessingle strand or multi-strand interpolation between two hair strands. Insome cases, the hair rendering system 124 employs multi-strandinterpolation between each given hair strand and its corresponding oneor two neighbor hair strands to generate the additional hair strands. Insome cases, a given hair strand is not associated with another hairstrand, and in such circumstances, the hair rendering system 124 employsthe single strand interpolation to generate the additional hair strands.

In some embodiments, after the additional hair strands are generated,the hair rendering system 124 renders a model of the hair style based onthe hair spline data file and the additional hair strands that aregenerated. In particular, the hair rendering system 124 renders adisplay of hair using the hair spline data in three passes for eachvideo frame that depicts a user's face. In a first pass of the threepasses: a geometry of the hair is generated using the hair spline dataand the additional hair strands; strand tangent directions are computedand stored in a red and green channel for each hair strand of theplurality of hair strands and the additional hair strands that have beengenerated; hair color luminance is stored in a blue channel for eachhair strand of the plurality of hair strands and the additional hairstrands that have been generated; and a one bit transparency is storedin an alpha channel for each hair strand of the plurality of hairstrands and the additional hair strands that have been generated. In asecond pass of the three passes, a screen quad is rendered based on thegeometry, the blue channel, and the alpha channel. In a third pass ofthe three passes, a one-dimensional Gaussian blur is performed on thescreen quad along the strand tangent directions stored in the red andgreen channels.

In some embodiments, after the additional hair strands are generated,the hair rendering system 124 renders a model of the hair style based onthe hair spline data file and the additional hair strands that aregenerated. In particular, the hair rendering system 124 renders adisplay of hair using the hair spline data in four passes for each videoframe. In a first pass of the four passes: a geometry of the hair isgenerated using the hair spline data and the additional hair strands;and an alpha color mask with additive blending is stored in an alphachannel for each hair strand of the plurality of hair strands and theadditional hair strands that have been generated. In a second pass ofthe four passes: strand tangent directions are computed and stored in ared and green channel for each hair strand of the plurality of hairstrands and the additional hair strands that have been generated; andhair color luminance is stored in a blue channel for each hair strand ofthe plurality of hair strands and the additional hair strands that havebeen generated. In a third pass of the four passes, a screen quad isrendered based on the geometry, the blue channel, and the alpha channel.In a fourth pass of the four passes, a one-dimensional Gaussian blur isperformed on the screen quad along the strand tangent directions storedin the red and green channels.

The application server 112 is communicatively coupled to a databaseserver 118, which facilitates access to a database 120 in which isstored data associated with messages processed by the messaging serverapplication 114. Database 120 may be a third-party database. Forexample, the application server 112 may be associated with a firstentity, and the database 120 or a portion of the database 120 may beassociated and hosted by a second different entity. In someimplementations, database 120 stores user data that the first entitycollects about various each of the users of a service provided by thefirst entity. For example, the user data includes user names, passwords,addresses, friends, activity information, preferences, videos or contentconsumed by the user, and so forth.

FIG. 2 is a schematic diagram 200 illustrating data, which may be storedin the database 120 of the messaging server system 108, according tocertain example embodiments. While the content of the database 120 isshown to comprise a number of tables, it will be appreciated that thedata could be stored in other types of data structures (e.g., as anobject-oriented database).

The database 120 includes message data stored within a message table214. An entity table 202 stores entity data, including an entity graph204. Entities for which records are maintained within the entity table202 may include individuals, corporate entities, organizations, objects,places, events, and so forth. Regardless of type, any entity regardingwhich the messaging server system 108 stores data may be a recognizedentity. Each entity is provided with a unique identifier, as well as anentity type identifier (not shown).

The entity graph 204 stores information regarding relationships andassociations between entities. Such relationships may be social,professional (e.g., work at a common corporation or organization),interest-based, or activity-based, merely for example.

Message table 214 may store a collection of conversations between a userand one or more friends or entities. Message table 214 may includevarious attributes of each conversation, such as the list ofparticipants, the size of the conversation (e.g., number of users and/ornumber of messages), the chat color of the conversation, a uniqueidentifier for the conversation, and any other conversation relatedfeature(s).

The database 120 also stores annotation data, in the example form offilters, in an annotation table 212. Database 120 also stores annotatedcontent received in the annotation table 212. Filters for which data isstored within the annotation table 212 are associated with and appliedto videos (for which data is stored in a video table 210) and/or images(for which data is stored in an image table 208). Filters, in oneexample, are overlays that are displayed as overlaid on an image orvideo during presentation to a recipient user. Filters may be of varioustypes, including user-selected filters from a gallery of filterspresented to a sending user by the messaging client application 104 whenthe sending user is composing a message. Other types of filters includegeolocation filters (also known as geo-filters), which may be presentedto a sending user based on geographic location. For example, geolocationfilters specific to a neighborhood or special location may be presentedwithin a UI by the messaging client application 104, based ongeolocation information determined by a Global Positioning System (GPS)unit of the client device 102. Another type of filter is a data filter,which may be selectively presented to a sending user by the messagingclient application 104, based on other inputs or information gathered bythe client device 102 during the message creation process. Examples ofdata filters include current temperature at a specific location, acurrent speed at which a sending user is traveling, battery life for aclient device 102, or the current time.

Other annotation data that may be stored within the image table 208 isso-called “lens” data. A “lens” may be a real-time special effect andsound that may be added to an image or a video.

As mentioned above, the video table 210 stores video data which, in oneembodiment, is associated with messages for which records are maintainedwithin the message table 214. Similarly, the image table 208 storesimage data associated with messages for which message data is stored inthe entity table 202. The entity table 202 may associate variousannotations from the annotation table 212 with various images and videosstored in the image table 208 and the video table 210.

Hair float texture 207 stores the hair spline data file for each hairstyle and/or for each frame of a video. The hair float texture 207stores data in floating point representation rather than integerrepresentation. As an example, the hair float texture 207 for one framemay include a red channel, a green channel, a blue channel, and an alphachannel for each of the plurality of hair strands. Three-dimensionalcoordinates (x-axis, y-axis, and z-axis) of each hair strand along aspline are stored in the red, green and blue channels of the hairstrand. The indices of or references to one or two other hair strandsdetermined to be neighbors of a given hair strand are stored in thealpha channel of the given hair strand. The indices may represent vertexpositions, such as single point three-dimensional coordinates of thestarting and/or ending position of the neighboring hair strands. Theindices or references may represent storage locations or sections of thehair float texture 207 that store coordinates of the neighboring hairstrands. In some implementations, hair float texture 207 is storedlocally on a user device used to generate the display of the hairstrands.

A story table 206 stores data regarding collections of messages andassociated image, video, or audio data, which are compiled into acollection (e.g., a story or a gallery). The creation of a particularcollection may be initiated by a particular user (e.g., each user forwhich a record is maintained in the entity table 202). A user may createa “personal story” in the form of a collection of content that has beencreated and sent/broadcast by that user. To this end, the UI of themessaging client application 104 may include an icon that isuser-selectable to enable a sending user to add specific content to hisor her personal story.

A collection may also constitute a “live story,” which is a collectionof content from multiple users that is created manually, automatically,or using a combination of manual and automatic techniques. For example,a “live story” may constitute a curated stream of user-submitted contentfrom various locations and events. Users whose client devices havelocation services enabled and are at a common location event at aparticular time may, for example, be presented with an option, via a UIof the messaging client application 104, to contribute content to aparticular live story. The live story may be identified to the user bythe messaging client application 104 based on his or her location. Theend result is a “live story” told from a community perspective.

A further type of content collection is known as a “location story,”which enables a user whose client device 102 is located within aspecific geographic location (e.g., on a college or university campus)to contribute to a particular collection. In some embodiments, acontribution to a location story may require a second degree ofauthentication to verify that the end user belongs to a specificorganization or other entity (e.g., is a student on the universitycampus).

FIG. 3 is a schematic diagram illustrating a structure of a message 300,according to some embodiments, generated by a messaging clientapplication 104 for communication to a further messaging clientapplication 104 or the messaging server application 114. The content ofa particular message 300 is used to populate the message table 214stored within the database 120, accessible by the messaging serverapplication 114. Similarly, the content of a message 300 is stored inmemory as “in-transit” or “in-flight” data of the client device 102 orthe application server 112. The message 300 is shown to include thefollowing components:

-   -   A message identifier 302: a unique identifier that identifies        the message 300.    -   A message text payload 304: text, to be generated by a user via        a UI of the client device 102 and that is included in the        message 300.    -   A message image payload 306: image data, captured by a camera        component of a client device 102 or retrieved from memory of a        client device 102, and that is included in the message 300.    -   A message video payload 308: video data, captured by a camera        component or retrieved from a memory component of the client        device 102 and that is included in the message 300.    -   A message audio payload 310: audio data, captured by a        microphone or retrieved from the memory component of the client        device 102, and that is included in the message 300.    -   Message annotations 312: annotation data (e.g., filters,        stickers, or other enhancements) that represents annotations to        be applied to message image payload 306, message video payload        308, or message audio payload 310 of the message 300.    -   A message duration parameter 314: parameter value indicating, in        seconds, the amount of time for which content of the message        (e.g., the message image payload 306, message video payload 308,        message audio payload 310) is to be presented or made accessible        to a user via the messaging client application 104.    -   A message geolocation parameter 316: geolocation data (e.g.,        latitudinal and longitudinal coordinates) associated with the        content payload of the message. Multiple message geolocation        parameter 316 values may be included in the payload, with each        of these parameter values being associated with respect to        content items included in the content (e.g., a specific image        within the message image payload 306, or a specific video in the        message video payload 308).    -   A message story identifier 318: identifier value identifying one        or more content collections (e.g., “stories”) with which a        particular content item in the message image payload 306 of the        message 300 is associated. For example, multiple images within        the message image payload 306 may each be associated with        multiple content collections using identifier values.    -   A message tag 320: each message 300 may be tagged with multiple        tags, each of which is indicative of the subject matter of        content included in the message payload. For example, where a        particular image included in the message image payload 306        depicts an animal (e.g., a lion), a tag value may be included        within the message tag 320 that is indicative of the relevant        animal. Tag values may be generated manually, based on user        input, or may be automatically generated using, for example,        image recognition.    -   A message sender identifier 322: an identifier (e.g., a        messaging system identifier, email address, or device        identifier) indicative of a user of the client device 102 on        which the message 300 was generated and from which the message        300 was sent.    -   A message receiver identifier 324: an identifier (e.g., a        messaging system identifier, email address, or device        identifier) indicative of user(s) of the client device 102 to        which the message 300 is addressed. In the case of a        conversation between multiple users, the identifier may indicate        each user involved in the conversation.

The contents (e.g., values) of the various components of message 300 maybe pointers to locations in tables within which content data values arestored. For example, an image value in the message image payload 306 maybe a pointer to (or address of) a location within an image table 208.Similarly, values within the message video payload 308 may point to datastored within a video table 210, values stored within the messageannotations 312 may point to data stored in an annotation table 212,values stored within the message story identifier 318 may point to datastored in a story table 206, and values stored within the message senderidentifier 322 and the message receiver identifier 324 may point to userrecords stored within an entity table 202.

FIG. 4 is a block diagram showing an example hair rendering system 124,according to example embodiments. Any one or more components orcombination of components shown in FIG. 4 can be implemented on a userdevices used to render a display of the hair strands. Hair renderingsystem 124 includes a hair strand input module 412, a hair strandneighbor identification module 414, a hair strand generation module 416,and a multi-pass hair rendering module 418. Hair strand input module 412receives a hair input file from a user that specifies (e.g., in floatingpoint format) the list of curves of each hair strand. In someimplementations, this file is created by a designer and provided tousers of a messaging client application 104. Once selected, the file isloaded into the hair strand input module 412. In some implementations, auser of the messaging client application 104 generates the hair filethat lists the curves for each hair strand and inputs that file to thehair strand input module 412.

The hair strand input module 412 loads the hair input file into storageand stores coordinates for each hair strand into an RGBA (red, green,blue alpha) float texture. The hair strand input module 412 stores inthe red, green and blue channel, the X, Y, and Z coordinates,respectively of each point of a spline of a hair strand that is input bythe user. The hair strand input module 412 collects spline points andcreates groups of hair strands by strand point numbers. In some cases,the hair strand input module 412 processes hair strands with the samepoint numbers in one pass and provides such hair strands to a simulatorfor processing together. The RGBA float texture includes multiplesections (in some cases referred to as indices). Each section includescoordinates in red, green, and blue channels of each point of aparticular hair strand. Each section may also include indices orreferences to other hair strands in the alpha channel of the particularhair strand to identify the section which stores the coordinates of theother hair strands.

The hair strand input module 412 provides the RGBA float texture to thehair strand neighbor identification module 414. The hair strand neighboridentification module 414 processes coordinates of each hair strand toidentify one or two neighbor hair strands of each hair strand. Once theone or two neighbor hair strands are identified, the hair strandneighbor identification module 414 stores the vertex points of, indicesor, or references to the neighbor hair strands in association with thegiven hair strand with which they are neighbors. To do so, the hairstrand neighbor identification module 414 stores the vertex points,references to, or index points of the neighbor hair strands in the alphachannel of the given hair strand. The index points or referencesidentify the storage locations in the RGBA float texture of thecoordinates of the spline points of the neighboring hair strand. As anexample, a RGBA float texture 702 that is generated and provided by thehair strand input module 412 is shown in FIG. 7A. RGBA float texture 702shows coordinates of four different hair strands. The first three rows711, 712, 713 show the coordinates stored respectively in the red, greenand blue channels of the RGBA float texture 702 for a first hair strand.The fourth row 714 shows the alpha channel in which the index points orvertex points of one or two neighbor hair strands identified for thefirst hair strand.

FIG. 7B shows an illustrative RGBA float texture 740 that includes 20sections representing coordinates of 20 hair strands. As shown, for hairstrand 0, the first section 0 includes in the red, green, and bluechannels 741 a-c, the spline points of the hair strand 0. In addition,two neighbors (hair strand 2 and hair strand 3) may be identified forhair strand 0. As a result, two respective index points or references tothe storage locations or sections in the RGBA float texture 740 of hairstrands 2 and 3 are stored in the alpha channel 741 of hair strand 0.The index points or references to the storage locations can be used toretrieve the section of the RGBA float texture 740 which stores thecoordinates in the red, green, and blue channels in the respectivesections of the hair strands. Specifically, the index point 2 identifiesthe section in the RGBA float texture 740 that stores the coordinates ofthe spline points of the hair strand 2 in the red, green, and bluechannels of hair strand 2. In some cases, no neighbors are associatedwith a given hair strand and in such cases no index points or referencesare stored in the alpha channel of the given hair strand. For example,hair strand 3 may not have any neighboring hair strands identified in aparticular frame and accordingly no index points or references arestored in the alpha channel 744 of the hair strand 3 alpha channel.

In some embodiments, the RGBA float texture 740 is updated for eachframe of video as hair strand spline points change positions. In suchcases, the neighboring hair strands may be identified and updated in theRGBA float texture 740 for each video frame.

As an example, the RGBA float texture 740 is used to interpolateadditional hair strands between hair strands based on the index orreferences stored in the alpha channels of each hair strand.Specifically, when strand 0 data is processed, positions of additionalhair strands are calculated using multiple hair strand interpolationtechniques between hair strand 0, hair strand 2 (referenced in the alphachannel of hair strand 0) and hair strand 3 (referenced in the alphachannel of hair strand 0). For hair strand 1, additional hair strandsare interpolated between hair strand 1 and hair strand 3 (referenced inthe alpha channel of hair strand 1). For hair strand 2, positions ofadditional hair strands are calculated between hair strand 2, hairstrand 4 (referenced in the alpha channel of hair strand 2) and hairstrand 10 (referenced in the alpha channel of hair strand 2). For hairstrand 3, additional hair strand generation is performed using a singlestrand interpolation technique because no neighbor hair strand indicesor references are stored in the alpha channel of hair strand 3.

In some implementations, the hair strand neighbor identification module414 performs a process described in connection with FIG. 6 to identifyneighbor hair strands. The hair strand neighbor identification module414 can identify neighbor hair strands using a nearest to current ornearest to next process. A user can specify whether to identifyneighbors using a nearest to current process or the nearest to nextprocess.

When the nearest to current process is selected, a radius that isspecified by the user is retrieved. Then, the hair strand neighboridentification module 414 can select to process the first hair strandthat is stored in the RGBA float texture 702. Once selected, the hairstrand neighbor identification module 414 can search within thespecified radius to identify all other hair strands that are stored inthe RGBA float texture 702. Specifically, the hair strand neighboridentification module 414 identifies a collection of other hair strandsbased on their coordinates stored in the RGBA float texture that arewithin the specified radius of the first hair strand. Once thecollection of hair strands is identified, the hair strand neighboridentification module 414 computes a distance between a vertex (or anyother point) of the first hair strand and each of the hair strands inthe collection. The hair strand neighbor identification module 414selects two neighboring hair strands in the collection that are closest,based on the computed distance, to the first hair strand than other hairstrands in the collection. The hair strand neighbor identificationmodule 414 stores the vertex points, index points of, or references tothe two neighboring hair strands that are selected in the alpha channelof the first hair strand. For example, as shown in diagram 701, anearest to current process is illustrated. In this process, a first hairstrand 721 is selected and a collection of hair strands is identifiedand shown in diagram 701. The hair strand neighbor identification module414 searches all the hair strands in the collection and determines thattwo neighboring hair strands 722 and 723 are closer to the first hairstrand 721 than all other hair strands in the collection.

The hair strand neighbor identification module 414 repeats the processof identifying neighbor hair strands for each hair strand that is storedin the RGBA float texture 702. For example, the hair strand neighboridentification module 414 selects a second hair strand and searches,using the nearest to current process, for two neighboring hair strandsthat are closer to the second hair strand than other hair strands in thecollection. The hair strand neighbor identification module 414 searchesfor the two neighboring hair strands relative to the second hair strandwithin the same radius as previously used to identify the collection.Namely, the collection of hair strands is identified once using thespecified radius and the neighboring hair strands are searched for eachhair strand within the collection. For example, the hair strand neighboridentification module 414 selects hair strand 723 and identifies twoother hair strands in the collection that are closer to hair strand 723than all other hair strands in the collection. The indices (orreferences to storage locations) of the two other hair strands are thenstored in the alpha channel for hair strand 723.

When the nearest to next process is selected, a radius that is specifiedby the user is retrieved and used for each hair strand that is selected.Then, the hair strand neighbor identification module 414 can select toprocess the first hair strand that is stored in the RGBA float texture702. Once selected, the hair strand neighbor identification module 414can search within the specified radius to identify all other hairstrands that are stored in the RGBA float texture 702. Specifically, thehair strand neighbor identification module 414 identifies a collectionof other hair strands based on their coordinates stored in the RGBAfloat texture that are within the specified radius of the first hairstrand. Once the collection of hair strands is identified, the hairstrand neighbor identification module 414 computes a distance between avertex (or any other point) of the first hair strand and each of thehair strands in the collection. The hair strand neighbor identificationmodule 414 selects one of the neighboring hair strands in the collectionthat is closest, based on the computed distance, to the first hairstrand than other hair strands in the collection. The hair strandneighbor identification module 414 stores the index points of orreferences to the neighboring hair strand that is selected in the alphachannel of the first hair strand.

The hair strand neighbor identification module 414 repeats this processby creating a new collection of hair strands that is within a radius ofa selected hair strand. For example, as shown in diagram 703, a nearestto next process is illustrated. In this process, a first hair strand 731is selected and a collection of hair strands is identified and shown indiagram 703. The hair strand neighbor identification module 414 searchesall the hair strands in the collection and determines that neighboringhair strand 732 is closer to the first hair strand 731 than all otherhair strands in the collection. The hair strand 732 is stored inassociation with the first hair strand 731. Then, the hair strand 732 isselected and a collection of hair strands is identified and shown indiagram 703 that is within a radius of the hair strand 732. The hairstrand neighbor identification module 414 searches all the hair strandsin the collection and determines that neighboring hair strand 733 iscloser to the second hair strand 732 than all other hair strands in thecollection. The index of or reference to hair strand 733 is stored inassociation with the second hair strand 732.

In some embodiments, in both the nearest to current and the nearest tonext process, once one or two neighboring hair strands that aredetermined to be closer to the first hair strand than other hair strandsin the collection are selected, the hair strand neighbor identificationmodule 414 can compute an angle between each of the two neighboring hairstrands and the first hair strand. Specifically, the hair strandneighbor identification module 414 can retrieve the coordinates of afirst of the two neighboring hair strands from the red, green, and bluechannel of the first of the two neighboring hair strands stored in theRGBA float texture 720. The hair strand neighbor identification module414 computes an angle between the first hair strand and the first of thetwo neighboring hair strands. If the computed angle is less than athreshold, the first of the two neighboring hair strands can remainstored in association with the first hair strand. If the computed angleis greater than the threshold, the hair strand neighbor identificationmodule 414 prevents the index of or reference to the first of the twoneighboring hair strands from being stored in the alpha channel of thefirst hair strand. In such cases, assuming the second of the twoneighboring hair strands is at an angle that is less than the thresholdof the first hair strand, only the index of or reference to the secondof the two neighboring hair strands is stored in association with thefirst hair strand in the alpha channel of the first hair strand.

The hair strand neighbor identification module 414 provides the RGBAfloat texture to the hair strand generation module 416. The hair strandgeneration module 416 processes the RGBA float texture and simulates orgenerates additional hair strands between a given hair strand that isstored in the RGBA float texture and one or two neighbor hair strands,whose indices or references are stored in the alpha channel for thegiven hair strand. To do so, the hair strand generation module 416performs single strand or multi-strand interpolation between thecoordinates of the given hair strand in the RGBA float texture and thecoordinates stored in the storage location identified by the index orreference of the one or two neighboring hair strands stored in the alphachannel of the given hair strand.

In the case of single strand interpolation, the hair strand generationmodule 416 generates additional strands around a base strand within aspecified radius (e.g., a radius input by a user). Single strandinterpolation can be used when a given hair strand in the RGBA floattexture does not have any neighboring hair strands stored in the alphachannel of the given hair strand (e.g., the alpha channel of the givenhair strand is empty). In the case of multi-strand interpolation,additional hair strands are generated between a given hair strand andone or two neighboring hair strands identified by the index or referencestored in the alpha channel of the given hair strand. To do so, atriangle having three edges is formed by connecting the vertex points ofthe base hair strand (e.g., the coordinates stored in the red, green,and blue channel of the given hair strand) and the vertex positions ofeach of two neighboring hair strands stored in the alpha channel of thebase hair strand. Once the triangle is formed, additional hair strandsare generated by interpolation within the confines of the triangleedges.

The hair strand generation module 416 populates the additional hairstrands that are generated by interpolation into the RGBA float textureand provides this updated RGBA float texture to the multi-pass hairrendering module 418. The multi-pass hair rendering module 418 processesthe RGBA float texture and renders a visual representation of the hairby creating triangles. An illustrative triangle strip is shown in FIG.7A. To avoid creation of many triangles, the multi-pass hair renderingmodule 418 uses instanced drawing, which creates a single triangle stripon initialization (e.g., hairstyle may have strands with maximum 25points number in which case the triangle strip is created with 50vertices and 48 triangles). This triangle strip is created and drawnonly once per frame, which keeps memory usage low and allows a greatnumber of triangles to be created fast. The hair strand points includingthe generated hair strands are read, every frame of a video, andtransformed to simulated strand point positions in a visual model. Themulti-pass hair rendering module 418 renders hair on an object (e.g., ahuman head or an animal or some other object depicted in a video orimage) in three or four passes for each frame or image.

FIG. 8A is a diagram illustrating a three pass approach. In a first pass(phase 1) of the three passes: multi-pass hair rendering module 418generates a geometry of the hair using the hair spline data and theadditional hair strands that are stored in the RGBA float texture. Themulti-pass hair rendering module 418 computes strand tangent directionsfor each hair strand in the RGBA float texture. Specifically, themulti-pass hair rendering module 418 generates a vector that indicates adirection between each pair of points of the spline that corresponds toeach hair strand. Namely, the multi-pass hair rendering module 418retrieves coordinates of a given hair strand and computes a vectorbetween each pair of points that form the given hair strand. Thesevectors that connect each pair of points are stored in a red and greenchannel for each hair strand of the plurality of hair strands and theadditional hair strands that have been generated. The multi-pass hairrendering module 418 stores hair color luminance of each hair strand ina blue channel and stores a one bit transparency of each hair strand inan alpha channel. In a second pass (phase 2) of the three passes, ascreen quad is rendered based on the geometry, the blue channel, and thealpha channel. In a third pass (phase 3) of the three passes, aone-dimensional Gaussian blur is performed on the screen quad along thestrand tangent directions stored in the red and green channels.

FIG. 8B is a diagram illustrating a three pass approach. In a first pass(phase 1) of the four passes: multi-pass hair rendering module 418generates a geometry of the hair using the hair spline data and theadditional hair strands that are stored in the RGBA float texture. Themulti-pass hair rendering module 418 stores an alpha color mask withadditive blending in an alpha channel for each hair strand. In a secondpass (phase 2) of the four passes: strand tangent directions arecomputed (in a similar manner as discussed above in connection with FIG.8A) and stored in a red and green channel for each hair strand. In thesecond pass, the multi-pass hair rendering module 418 also stores haircolor luminance in a blue channel for each hair strand. In a third pass(phase 3) of the four passes, multi-pass hair rendering module 418renders a screen quad based on the geometry of the hair, the bluechannel, and the alpha channel. In a fourth pass (phase 4) of the fourpasses, a one-dimensional Gaussian blur is performed on the screen quadalong the strand tangent directions stored in the red and greenchannels.

FIG. 5 is a flowchart illustrating example operations of the hairrendering system 124 in performing process 500, according to exampleembodiments. The process 500 may be embodied in computer-readableinstructions for execution by one or more processors such that theoperations of the process 500 may be performed in part or in whole bythe functional components of the messaging server system 108 and/orthird-party application 105; accordingly, the process 500 is describedbelow by way of example with reference thereto. However, in otherembodiments, at least some of the operations of the process 500 may bedeployed on various other hardware configurations. The process 500 istherefore not intended to be limited to the messaging server system 108and can be implemented in whole, or in part, by any other component.Some or all of the operations of process 500 can be in parallel, out oforder, or entirely omitted.

At operation 501, the hair rendering system 124 receives hair splinedata comprising coordinates of a plurality of hair strands.

At operation 502, the hair rendering system 124 selects a first hairstrand of the plurality of hair strands.

At operation 503, the hair rendering system 124 retrieves coordinates ofthe first hair strand.

At operation 504, the hair rendering system 124 identifies, based on therespective coordinates of the plurality of hair strands, a second hairstrand that is adjacent to the first hair strand.

At operation 505, the hair rendering system 124 stores a reference tothe second hair strand in association with the coordinates of the firsthair strand.

At operation 506, the hair rendering system 124 generates one or moreadditional hair strands between the first hair strand and the secondhair strand based on the coordinates of the first hair strand and thereference to the second hair strand.

FIG. 6 is a flowchart illustrating example operations of the hairrendering system 124 in performing process 600, according to exampleembodiments. The process 600 may be embodied in computer-readableinstructions for execution by one or more processors such that theoperations of the process 600 may be performed in part or in whole bythe functional components of the messaging server system 108 and/orthird-party application 105; accordingly, the process 600 is describedbelow by way of example with reference thereto. However, in otherembodiments, at least some of the operations of the process 600 may bedeployed on various other hardware configurations. The process 600 istherefore not intended to be limited to the messaging server system 108and can be implemented in whole, or in part, by any other component.Some or all of the operations of process 600 can be in parallel, out oforder, or entirely omitted.

At operation 601, the hair rendering system 124 receives inputsspecifying a radius.

At operation 602, the hair rendering system 124 determines what type ofsearch algorithm is specified. In response to determining that a nearestto current search algorithm is specified, the hair rendering system 124proceeds to operation 603. In response to determining that a nearest tonext search algorithm is specified, the hair rendering system 124proceeds to operation 608.

At operation 603, the hair rendering system 124 identifies a collectionof hair strands that is within the specified radius of the given hairstrand.

At operation 604, the hair rendering system 124 selects a given hairstrand in the collection of hair strands.

At operation 605, the hair rendering system 124 computes a distancebetween the given hair strand and each of the hair strands in thecollection of hair strands.

At operation 606, the hair rendering system 124 identifies, as neighborhair strands, two of the hair strands in the collection that are closestin distance to the given hair strand than other hair strands in thecollection of hair strands and/or that satisfy an angle threshold.

At operation 607, the hair rendering system 124 determines if additionalhair strands remain to be processed and if so, the hair rendering system124 proceeds to operation 604. Otherwise, the hair rendering system 124ends the process.

At operation 608, the hair rendering system 124 selects a given hairstrand.

At operation 609, the hair rendering system 124 identifies a collectionof hair strands that is within the specified radius of the given hairstrand.

At operation 610, the hair rendering system 124 computes a distancebetween the given hair strand and each of the hair strands in thecollection of hair strands.

At operation 611, the hair rendering system 124 identifies, as aneighbor hair strand, one of the hair strands in the collection that isclosest in distance to the given hair strand than other hair strands inthe collection of hair strands and/or that satisfies an angle threshold.

At operation 612, the hair rendering system 124 determines if additionalhair strands remain to be processed and if so, the hair rendering system124 proceeds to operation 608. Otherwise, the hair rendering system 124ends the process.

FIG. 9 is a block diagram illustrating an example software architecture906, which may be used in conjunction with various hardwarearchitectures herein described. FIG. 9 is a non-limiting example of asoftware architecture and it will be appreciated that many otherarchitectures may be implemented to facilitate the functionalitydescribed herein. The software architecture 906 may execute on hardwaresuch as machine 1000 of FIG. 10 that includes, among other things,processors 1004, memory 1014, and input/output (I/O) components 1018. Arepresentative hardware layer 952 is illustrated and can represent, forexample, the machine 1000 of FIG. 10 . The representative hardware layer952 includes a processing unit 954 having associated executableinstructions 904. Executable instructions 904 represent the executableinstructions of the software architecture 906, including implementationof the methods, components, and so forth described herein. The hardwarelayer 952 also includes memory and/or storage modules memory/storage956, which also have executable instructions 904. The hardware layer 952may also comprise other hardware 958.

In the example architecture of FIG. 9 , the software architecture 906may be conceptualized as a stack of layers where each layer providesparticular functionality. For example, the software architecture 906 mayinclude layers such as an operating system 902, libraries 920,frameworks/middleware 918, applications 916, and a presentation layer914. Operationally, the applications 916 and/or other components withinthe layers may invoke API calls 908 through the software stack andreceive messages 912 in response to the API calls 908. The layersillustrated are representative in nature and not all softwarearchitectures have all layers. For example, some mobile or specialpurpose operating systems may not provide a frameworks/middleware 918,while others may provide such a layer. Other software architectures mayinclude additional or different layers.

The operating system 902 may manage hardware resources and providecommon services. The operating system 902 may include, for example, akernel 922, services 924, and drivers 926. The kernel 922 may act as anabstraction layer between the hardware and the other software layers.For example, the kernel 922 may be responsible for memory management,processor management (e.g., scheduling), component management,networking, security settings, and so on. The services 924 may provideother common services for the other software layers. The drivers 926 areresponsible for controlling or interfacing with the underlying hardware.For instance, the drivers 926 include display drivers, camera drivers,Bluetooth® drivers, flash memory drivers, serial communication drivers(e.g., Universal Serial Bus (USB) drivers), Wi-Fi® drivers, audiodrivers, power management drivers, and so forth depending on thehardware configuration.

The libraries 920 provide a common infrastructure that is used by theapplications 916 and/or other components and/or layers. The libraries920 provide functionality that allows other software components toperform tasks in an easier fashion than to interface directly with theunderlying operating system 902 functionality (e.g., kernel 922,services 924 and/or drivers 926). The libraries 920 may include systemlibraries 944 (e.g., C standard library) that may provide functions suchas memory allocation functions, string manipulation functions,mathematical functions, and the like. In addition, the libraries 920 mayinclude API libraries 946 such as media libraries (e.g., libraries tosupport presentation and manipulation of various media format such asMPREG4, H.264, MP3, AAC, AMR, JPG, PNG), graphics libraries (e.g., anOpenGL framework that may be used to render two-dimensional andthree-dimensional in a graphic content on a display), database libraries(e.g., SQLite that may provide various relational database functions),web libraries (e.g., WebKit that may provide web browsingfunctionality), and the like. The libraries 920 may also include a widevariety of other libraries 948 to provide many other APIs to theapplications 916 and other software components/modules.

The frameworks/middleware 918 (also sometimes referred to as middleware)provide a higher-level common infrastructure that may be used by theapplications 916 and/or other software components/modules. For example,the frameworks/middleware 918 may provide various graphic user interfacefunctions, high-level resource management, high-level location services,and so forth. The frameworks/middleware 918 may provide a broad spectrumof other APIs that may be utilized by the applications 916 and/or othersoftware components/modules, some of which may be specific to aparticular operating system 902 or platform.

The applications 916 include built-in applications 938 and/orthird-party applications 940. Examples of representative built-inapplications 938 may include, but are not limited to, a contactsapplication, a browser application, a book reader application, alocation application, a media application, a messaging application,and/or a game application. Third-party applications 940 may include anapplication developed using the ANDROID™ or IOS™ software developmentkit (SDK) by an entity other than the vendor of the particular platform,and may be mobile software running on a mobile operating system such asIOS™, ANDROID™, WINDOWS® Phone, or other mobile operating systems. Thethird-party applications 940 may invoke the API calls 908 provided bythe mobile operating system (such as operating system 902) to facilitatefunctionality described herein.

The applications 916 may use built-in operating system functions (e.g.,kernel 922, services 924, and/or drivers 926), libraries 920, andframeworks/middleware 918 to create UIs to interact with users of thesystem. Alternatively, or additionally, in some systems, interactionswith a user may occur through a presentation layer, such as presentationlayer 914. In these systems, the application/component “logic” can beseparated from the aspects of the application/component that interactwith a user.

FIG. 10 is a block diagram illustrating components of a machine 1000,according to some example embodiments, able to read instructions from amachine-readable medium (e.g., a machine-readable storage medium) andperform any one or more of the methodologies discussed herein.Specifically, FIG. 10 shows a diagrammatic representation of the machine1000 in the example form of a computer system, within which instructions1010 (e.g., software, a program, an application, an applet, an app, orother executable code) for causing the machine 1000 to perform any oneor more of the methodologies discussed herein may be executed. As such,the instructions 1010 may be used to implement modules or componentsdescribed herein. The instructions 1010 transform the general,non-programmed machine 1000 into a particular machine 1000 programmed tocarry out the described and illustrated functions in the mannerdescribed. In alternative embodiments, the machine 1000 operates as astandalone device or may be coupled (e.g., networked) to other machines.In a networked deployment, the machine 1000 may operate in the capacityof a server machine or a client machine in a server-client networkenvironment, or as a peer machine in a peer-to-peer (or distributed)network environment. The machine 1000 may comprise, but not be limitedto, a server computer, a client computer, a personal computer (PC), atablet computer, a laptop computer, a netbook, a set-top box (STB), apersonal digital assistant (PDA), an entertainment media system, acellular telephone, a smart phone, a mobile device, a wearable device(e.g., a smart watch), a smart home device (e.g., a smart appliance),other smart devices, a web appliance, a network router, a networkswitch, a network bridge, or any machine capable of executing theinstructions 1010, sequentially or otherwise, that specify actions to betaken by machine 1000. Further, while only a single machine 1000 isillustrated, the term “machine” shall also be taken to include acollection of machines that individually or jointly execute theinstructions 1010 to perform any one or more of the methodologiesdiscussed herein.

The machine 1000 may include processors 1004, memory/storage 1006, andI/O components 1018, which may be configured to communicate with eachother such as via a bus 1002. In an example embodiment, the processors1004 (e.g., a central processing unit (CPU), a reduced instruction setcomputing (RISC) processor, a complex instruction set computing (CISC)processor, a graphics processing unit (GPU), a digital signal processor(DSP), an application-specific integrated circuit (ASIC), aradio-frequency integrated circuit (RFIC), another processor, or anysuitable combination thereof) may include, for example, a processor 1008and a processor 1012 that may execute the instructions 1010. The term“processor” is intended to include multi-core processors 1004 that maycomprise two or more independent processors (sometimes referred to as“cores”) that may execute instructions contemporaneously. Although FIG.10 shows multiple processors 1004, the machine 1000 may include a singleprocessor with a single core, a single processor with multiple cores(e.g., a multi-core processor), multiple processors with a single core,multiple processors with multiple cores, or any combination thereof.

The memory/storage 1006 may include a memory 1014, such as a mainmemory, or other memory storage, and a storage unit 1016, bothaccessible to the processors 1004 such as via the bus 1002. The storageunit 1016 and memory 1014 store the instructions 1010 embodying any oneor more of the methodologies or functions described herein. Theinstructions 1010 may also reside, completely or partially, within thememory 1014, within the storage unit 1016, within at least one of theprocessors 1004 (e.g., within the processor's cache memory), or anysuitable combination thereof, during execution thereof by the machine1000. Accordingly, the memory 1014, the storage unit 1016, and thememory of processors 1004 are examples of machine-readable media.

The I/O components 1018 may include a wide variety of components toreceive input, provide output, produce output, transmit information,exchange information, capture measurements, and so on. The specific I/Ocomponents 1018 that are included in a particular machine 1000 willdepend on the type of machine. For example, portable machines such asmobile phones will likely include a touch input device or other suchinput mechanisms, while a headless server machine will likely notinclude such a touch input device. It will be appreciated that the I/Ocomponents 1018 may include many other components that are not shown inFIG. 10 . The I/O components 1018 are grouped according to functionalitymerely for simplifying the following discussion and the grouping is inno way limiting. In various example embodiments, the I/O components 1018may include output components 1026 and input components 1028. The outputcomponents 1026 may include visual components (e.g., a display such as aplasma display panel (PDP), a light emitting diode (LED) display, aliquid crystal display (LCD), a projector, or a cathode ray tube (CRT)),acoustic components (e.g., speakers), haptic components (e.g., avibratory motor, resistance mechanisms), other signal generators, and soforth. The input components 1028 may include alphanumeric inputcomponents (e.g., a keyboard, a touch screen configured to receivealphanumeric input, a photo-optical keyboard, or other alphanumericinput components), point-based input components (e.g., a mouse, atouchpad, a trackball, a joystick, a motion sensor, or other pointinginstrument), tactile input components (e.g., a physical button, a touchscreen that provides location and/or force of touches or touch gestures,or other tactile input components), audio input components (e.g., amicrophone), and the like.

In further example embodiments, the I/O components 1018 may includebiometric components 1039, motion components 1034, environmentalcomponents 1036, or position components 1038 among a wide array of othercomponents. For example, the biometric components 1039 may includecomponents to detect expressions (e.g., hand expressions, facialexpressions, vocal expressions, body gestures, or eye tracking), measurebiosignals (e.g., blood pressure, heart rate, body temperature,perspiration, or brain waves), identify a person (e.g., voiceidentification, retinal identification, facial identification,fingerprint identification, or electroencephalogram basedidentification), and the like. The motion components 1034 may includeacceleration sensor components (e.g., accelerometer), gravitation sensorcomponents, rotation sensor components (e.g., gyroscope), and so forth.The environmental components 1036 may include, for example, illuminationsensor components (e.g., photometer), temperature sensor components(e.g., one or more thermometer that detect ambient temperature),humidity sensor components, pressure sensor components (e.g.,barometer), acoustic sensor components (e.g., one or more microphonesthat detect background noise), proximity sensor components (e.g.,infrared sensors that detect nearby objects), gas sensors (e.g., gasdetection sensors to detection concentrations of hazardous gases forsafety or to measure pollutants in the atmosphere), or other componentsthat may provide indications, measurements, or signals corresponding toa surrounding physical environment. The position components 1038 mayinclude location sensor components (e.g., a GPS receiver component),altitude sensor components (e.g., altimeters or barometers that detectair pressure from which altitude may be derived), orientation sensorcomponents (e.g., magnetometers), and the like.

Communication may be implemented using a wide variety of technologies.The I/O components 1018 may include communication components 1040operable to couple the machine 1000 to a network 1037 or devices 1029via coupling 1024 and coupling 1022, respectively. For example, thecommunication components 1040 may include a network interface componentor other suitable device to interface with the network 1037. In furtherexamples, communication components 1040 may include wired communicationcomponents, wireless communication components, cellular communicationcomponents, Near Field Communication (NFC) components, Bluetooth®components (e.g., Bluetooth® Low Energy), Wi-Fi® components, and othercommunication components to provide communication via other modalities.The devices 1029 may be another machine or any of a wide variety ofperipheral devices (e.g., a peripheral device coupled via a USB).

Moreover, the communication components 1040 may detect identifiers orinclude components operable to detect identifiers. For example, thecommunication components 1040 may include Radio Frequency Identification(RFID) tag reader components, NFC smart tag detection components,optical reader components (e.g., an optical sensor to detectone-dimensional bar codes such as Universal Product Code (UPC) bar code,multi-dimensional bar codes such as Quick Response (QR) code, Azteccode, Data Matrix, Dataglyph, MaxiCode, PDF417, Ultra Code, UCC RSS-2Dbar code, and other optical codes), or acoustic detection components(e.g., microphones to identify tagged audio signals). In addition, avariety of information may be derived via the communication components1040, such as location via Internet Protocol (IP) geo-location, locationvia Wi-Fi® signal triangulation, location via detecting a NFC beaconsignal that may indicate a particular location, and so forth.

Glossary

“CARRIER SIGNAL” in this context refers to any intangible medium that iscapable of storing, encoding, or carrying transitory or non-transitoryinstructions for execution by the machine, and includes digital oranalog communications signals or other intangible medium to facilitatecommunication of such instructions. Instructions may be transmitted orreceived over the network using a transitory or non-transitorytransmission medium via a network interface device and using any one ofa number of well-known transfer protocols.

“CLIENT DEVICE” in this context refers to any machine that interfaces toa communications network to obtain resources from one or more serversystems or other client devices. A client device may be, but is notlimited to, a mobile phone, desktop computer, laptop, PDAs, smartphones, tablets, ultra books, netbooks, laptops, multi-processorsystems, microprocessor-based or programmable consumer electronics, gameconsoles, set-top boxes, or any other communication device that a usermay use to access a network.

“COMMUNICATIONS NETWORK” in this context refers to one or more portionsof a network that may be an ad hoc network, an intranet, an extranet, avirtual private network (VPN), a local area network (LAN), a wirelessLAN (WLAN), a wide area network (WAN), a wireless WAN (WWAN), ametropolitan area network (MAN), the Internet, a portion of theInternet, a portion of the Public Switched Telephone Network (PSTN), aplain old telephone service (POTS) network, a cellular telephonenetwork, a wireless network, a Wi-Fi® network, another type of network,or a combination of two or more such networks. For example, a network ora portion of a network may include a wireless or cellular network andthe coupling may be a Code Division Multiple Access (CDMA) connection, aGlobal System for Mobile communications (GSM) connection, or other typeof cellular or wireless coupling. In this example, the coupling mayimplement any of a variety of types of data transfer technology, such asSingle Carrier Radio Transmission Technology (1×RTT), Evolution-DataOptimized (EVDO) technology, General Packet Radio Service (GPRS)technology, Enhanced Data rates for GSM Evolution (EDGE) technology,third Generation Partnership Project (3GPP) including 3G, fourthgeneration wireless (4G) networks, Universal Mobile TelecommunicationsSystem (UMTS), High Speed Packet Access (HSPA), WorldwideInteroperability for Microwave Access (WiMAX), Long Term Evolution (LTE)standard, others defined by various standard setting organizations,other long range protocols, or other data transfer technology.

“EPHEMERAL MESSAGE” in this context refers to a message that isaccessible for a time-limited duration. An ephemeral message may be atext, an image, a video, and the like. The access time for the ephemeralmessage may be set by the message sender. Alternatively, the access timemay be a default setting or a setting specified by the recipient.Regardless of the setting technique, the message is transitory.

“MACHINE-READABLE MEDIUM” in this context refers to a component, device,or other tangible media able to store instructions and data temporarilyor permanently and may include, but is not limited to, random-accessmemory (RAM), read-only memory (ROM), buffer memory, flash memory,optical media, magnetic media, cache memory, other types of storage(e.g., Erasable Programmable Read-Only Memory (EEPROM)) and/or anysuitable combination thereof. The term “machine-readable medium” shouldbe taken to include a single medium or multiple media (e.g., acentralized or distributed database, or associated caches and servers)able to store instructions. The term “machine-readable medium” shallalso be taken to include any medium, or combination of multiple media,that is capable of storing instructions (e.g., code) for execution by amachine, such that the instructions, when executed by one or moreprocessors of the machine, cause the machine to perform any one or moreof the methodologies described herein. Accordingly, a “machine-readablemedium” refers to a single storage apparatus or device, as well as“cloud-based” storage systems or storage networks that include multiplestorage apparatus or devices. The term “machine-readable medium”excludes signals per se.

“COMPONENT” in this context refers to a device, physical entity, orlogic having boundaries defined by function or subroutine calls, branchpoints, APIs, or other technologies that provide for the partitioning ormodularization of particular processing or control functions. Componentsmay be combined via their interfaces with other components to carry outa machine process. A component may be a packaged functional hardwareunit designed for use with other components and a part of a program thatusually performs a particular function of related functions. Componentsmay constitute either software components (e.g., code embodied on amachine-readable medium) or hardware components. A “hardware component”is a tangible unit capable of performing certain operations and may beconfigured or arranged in a certain physical manner. In various exampleembodiments, one or more computer systems (e.g., a standalone computersystem, a client computer system, or a server computer system) or one ormore hardware components of a computer system (e.g., a processor or agroup of processors) may be configured by software (e.g., an applicationor application portion) as a hardware component that operates to performcertain operations as described herein.

A hardware component may also be implemented mechanically,electronically, or any suitable combination thereof. For example, ahardware component may include dedicated circuitry or logic that ispermanently configured to perform certain operations. A hardwarecomponent may be a special-purpose processor, such as aField-Programmable Gate Array (FPGA) or an ASIC. A hardware componentmay also include programmable logic or circuitry that is temporarilyconfigured by software to perform certain operations. For example, ahardware component may include software executed by a general-purposeprocessor or other programmable processor. Once configured by suchsoftware, hardware components become specific machines (or specificcomponents of a machine) uniquely tailored to perform the configuredfunctions and are no longer general-purpose processors. It will beappreciated that the decision to implement a hardware componentmechanically, in dedicated and permanently configured circuitry, or intemporarily configured circuitry (e.g., configured by software) may bedriven by cost and time considerations. Accordingly, the phrase“hardware component” (or “hardware-implemented component”) should beunderstood to encompass a tangible entity, be that an entity that isphysically constructed, permanently configured (e.g., hardwired), ortemporarily configured (e.g., programmed) to operate in a certain manneror to perform certain operations described herein. Consideringembodiments in which hardware components are temporarily configured(e.g., programmed), each of the hardware components need not beconfigured or instantiated at any one instance in time. For example,where a hardware component comprises a general-purpose processorconfigured by software to become a special-purpose processor, thegeneral-purpose processor may be configured as respectively differentspecial-purpose processors (e.g., comprising different hardwarecomponents) at different times. Software accordingly configures aparticular processor or processors, for example, to constitute aparticular hardware component at one instance of time and to constitutea different hardware component at a different instance of time.

Hardware components can provide information to, and receive informationfrom, other hardware components. Accordingly, the described hardwarecomponents may be regarded as being communicatively coupled. Wheremultiple hardware components exist contemporaneously, communications maybe achieved through signal transmission (e.g., over appropriate circuitsand buses) between or among two or more of the hardware components. Inembodiments in which multiple hardware components are configured orinstantiated at different times, communications between such hardwarecomponents may be achieved, for example, through the storage andretrieval of information in memory structures to which the multiplehardware components have access. For example, one hardware component mayperform an operation and store the output of that operation in a memorydevice to which it is communicatively coupled. A further hardwarecomponent may then, at a later time, access the memory device toretrieve and process the stored output.

Hardware components may also initiate communications with input oroutput devices, and can operate on a resource (e.g., a collection ofinformation). The various operations of example methods described hereinmay be performed, at least partially, by one or more processors that aretemporarily configured (e.g., by software) or permanently configured toperform the relevant operations. Whether temporarily or permanentlyconfigured, such processors may constitute processor-implementedcomponents that operate to perform one or more operations or functionsdescribed herein. As used herein, “processor-implemented component”refers to a hardware component implemented using one or more processors.Similarly, the methods described herein may be at least partiallyprocessor-implemented, with a particular processor or processors beingan example of hardware. For example, at least some of the operations ofa method may be performed by one or more processors orprocessor-implemented components. Moreover, the one or more processorsmay also operate to support performance of the relevant operations in a“cloud computing” environment or as a “software as a service” (SaaS).For example, at least some of the operations may be performed by a groupof computers (as examples of machines including processors), with theseoperations being accessible via a network (e.g., the Internet) and viaone or more appropriate interfaces (e.g., an API). The performance ofcertain of the operations may be distributed among the processors, notonly residing within a single machine, but deployed across a number ofmachines. In some example embodiments, the processors orprocessor-implemented components may be located in a single geographiclocation (e.g., within a home environment, an office environment, or aserver farm). In other example embodiments, the processors orprocessor-implemented components may be distributed across a number ofgeographic locations.

“PROCESSOR” in this context refers to any circuit or virtual circuit (aphysical circuit emulated by logic executing on an actual processor)that manipulates data values according to control signals (e.g.,“commands,” “op codes,” “machine code,” etc.) and which producescorresponding output signals that are applied to operate a machine. Aprocessor may, for example, be a Central Processing Unit (CPU), aReduced Instruction Set Computing (RISC) processor, a ComplexInstruction Set Computing (CISC) processor, a Graphics Processing Unit(GPU), a Digital Signal Processor (DSP), an ASIC, a Radio-FrequencyIntegrated Circuit (RFIC) or any combination thereof. A processor mayfurther be a multi-core processor having two or more independentprocessors (sometimes referred to as “cores”) that may executeinstructions contemporaneously.

“TIMESTAMP” in this context refers to a sequence of characters orencoded information identifying when a certain event occurred, forexample giving date and time of day, sometimes accurate to a smallfraction of a second.

Changes and modifications may be made to the disclosed embodimentswithout departing from the scope of the present disclosure. These andother changes or modifications are intended to be included within thescope of the present disclosure, as expressed in the following claims.

What is claimed is:
 1. A method comprising: receiving, by one or moreprocessors, a digital representation of a three-dimensional (3D) objectcomprising a surface having a plurality of strands; selecting, by theone or more processors, a first strand of the plurality of strands;determining that an attribute of the first strand satisfies apredetermined criterion; identifying, by the one or more processors, oneor more additional strands that are adjacent to the first strand;analyzing, by the one or more processors, the attribute of each of theidentified additional strands to determine whether each additionalstrand satisfies the predetermined criterion; and in response todetermining that at least one of the identified additional strandssatisfies the predetermined criterion, generating, by the one or moreprocessors, one or more additional strands between the first strand andthe at least one identified additional strand.
 2. The method of claim 1,further comprising receiving spline data comprising coordinates of theplurality of strands.
 3. The method of claim 1, further comprising:retrieving coordinates of the first strand; identifying, based onrespective coordinates of the plurality of strands, a second strand thatis adjacent to the first strand; and storing a reference to the secondstrand in association with the coordinates of the first strand.
 4. Themethod of claim 1, wherein the one or more additional strands aregenerated based on coordinates of the first strand and a reference to asecond strand.
 5. The method of claim 1, further comprising: receivinginput specifying a radius; and identifying a collection of strands thatis within the specified radius of the first strand.
 6. The method ofclaim 1, further comprising: searching coordinates of the plurality ofstrands, based on coordinates of the first strand, to identify a thirdstrand of the plurality of strands that is adjacent to the first strand;and storing a reference to the third strand in association thecoordinates of the first strand.
 7. The method of claim 6, wherein thesearching comprises: receiving input specifying a radius; identifying acollection of strands that is within the specified radius of the firststrand; computing a distance between the first strand and each of thestrands in the collection of strands; and identifying, as a secondstrand and the third strand, two of the strands in the collection thatare closest in distance to the first strand than other strands in thecollection of strands.
 8. The method of claim 1, wherein coordinates ofthe plurality of strands are stored in a floating texture comprising ared channel, a green channel, a blue channel, and an alpha channel foreach of the plurality of strands, wherein 3D coordinates of the firststrand are stored in the red, green, and blue channels of the firststrand, and wherein a reference to a second strand is stored in thealpha channel of the first strand.
 9. The method of claim 1, furthercomprising: determining that an additional angle between the firststrand and a third strand exceeds a threshold; and preventing areference to the third strand from being stored in association withcoordinates of the first strand in response to determining that theadditional angle exceeds the threshold.
 10. The method of claim 1,wherein generating the additional strands comprises performing singlestrand or multi-strand interpolation, wherein single strandinterpolation is performed instead of multi-strand interpolation inresponse to determining that coordinates of a given strand are notassociated with other strands.
 11. The method of claim 1, wherein: in afirst pass of three passes: a geometry is generated using the additionalstrands; strand tangent directions are computed and stored in a red andgreen channel for each strand of the plurality of strands and theadditional strands that have been generated; color luminance is storedin a blue channel for each strand of the plurality of strands and theadditional strands that have been generated; and a one bit transparencyis stored in an alpha channel for each strand of the plurality ofstrands and the additional strands that have been generated; in a secondpass of the three passes, a screen quad is rendered based on thegeometry, the blue channel, and the alpha channel; and in a third passof the three passes, a one-dimensional Gaussian blur is performed on thescreen quad along the strand tangent directions stored in the red andgreen channels.
 12. The method of claim 1, wherein: in a first pass offour passes: a geometry is generated using the additional strands; andan alpha color mask with additive blending is stored in an alpha channelfor each strand of the plurality of strands and the additional strandsthat have been generated; in a second pass of the four passes: strandtangent directions are computed and stored in a red and green channelfor each strand of the plurality of strands and the additional strandsthat have been generated; and color luminance is stored in a bluechannel for each strand of the plurality of strands and the additionalstrands that have been generated; in a third pass of the four passes, ascreen quad is rendered based on the geometry, the blue channel, and thealpha channel; and in a fourth pass of the four passes, aone-dimensional Gaussian blur is performed on the screen quad along thestrand tangent directions stored in the red and green channels.
 13. Themethod of claim 1, wherein a number of additional strands that aregenerated is selected by a user input.
 14. The method of claim 1,further comprising: determining whether resources of a device satisfyminimum resource constraints; and in response to determining that theresources of the device satisfy the minimum resource constraints,rendering a display simulating different strand groups in the pluralityof strands and the additional strands.
 15. The method of claim 1,further comprising: determining whether resources of a device satisfyminimum resource constraints; and in response to determining that theresources of the device fail to satisfy the minimum resourceconstraints, rendering a display based on a static geometry generatedbased on the plurality of strands and the additional strands.
 16. Asystem comprising: at least one processor configured to performoperations comprising: receiving a digital representation of athree-dimensional (3D) object comprising a surface having a plurality ofstrands; selecting a first strand of the plurality of strands;determining that an attribute of the first strand satisfies apredetermined criterion; identifying one or more additional strands thatare adjacent to the first strand; analyzing the attribute of each of theidentified additional strands to determine whether each additionalstrand satisfies the predetermined criterion; and in response todetermining that at least one of the identified additional strandssatisfies the predetermined criterion, generating one or more additionalstrands between the first strand and the at least one identifiedadditional strand.
 17. The system of claim 16, wherein the operationsfurther comprise receiving spline data comprising coordinates of theplurality of strands.
 18. The system of claim 16, wherein the operationsfurther comprise: retrieving coordinates of the first strand;identifying, based on respective coordinates of the plurality ofstrands, a second strand that is adjacent to the first strand; andstoring a reference to the second strand in association with thecoordinates of the first strand.
 19. The system of claim 16, wherein theone or more additional strands are generated based on coordinates of thefirst strand and a reference to a second strand.
 20. A non-transitorymachine-readable storage medium that includes instructions that, whenexecuted by at least one processor of a machine, cause the machine toperform operations comprising: receiving a digital representation of athree-dimensional (3D) object comprising a surface having a plurality ofstrands; selecting a first strand of the plurality of strands;determining that an attribute of the first strand satisfies apredetermined criterion; identifying one or more additional strands thatare adjacent to the first strand; analyzing the attribute of each of theidentified additional strands to determine whether each additionalstrand satisfies the predetermined criterion; and in response todetermining that at least one of the identified additional strandssatisfies the predetermined criterion, generating one or more additionalstrands between the first strand and the at least one identifiedadditional strand.